Different risk models at banks have been a troubling issue over the last several years for both regulators and market participants. The basic problem has been a lack of apples-to-apples analysis in how banks report risk and hence their capital ratios. Taking another swing at making a solution, the Basel Committee last week released a new methodology on operational risk.
In “Standardised Measurement Approach for operational risk,” a consultative document issued on March 4, 2016, the Basel Committee presents one methodology for measuring operational risk that would be used by all banks. Importantly, they remove the option for the Advanced Measurement Approach (AMA). Although the AMA offered flexibility when created in 2006, the Committee notes that:

Supervisory experience with the AMA has been mixed. The inherent complexity of the AMA and the lack of comparability arising from a wide range of internal modelling practices have exacerbated variability in risk-weighted asset calculations, and have eroded confidence in risk-weighted capital ratios.

And that there is the meat of the problem. The range of options that banks have under advanced approaches, including differences between the Standardised and Advanced Approaches in measuring counterparty credit risk, mean that the final resulting numbers don’t necessarily mean much anymore. Banks have told us that moving from a Standardised to Advanced Approach creates very meaningful capital savings, but the various methodologies used for calculating an Advanced Approach doesn’t line up for comparison anywhere.
In operational risk, the proposed single method will be the Standardised Measurement Approach (SMA). A primary input to the SMA is the Business Indicator (BI). According to the Committee:

The SMA combines the Business Indicator (BI), a simple financial statement proxy of operational risk exposure, with bank-specific operational loss data… The BI is made up of almost the same P&L items that are found in the composition of Gross Income (GI). The main difference relates to how the items are combined. The BI uses positive values of its components, thereby avoiding counterintuitive negative contributions from some of the bank’s businesses to the capital charge (eg negative P&L on the trading book), which is possible under the GI. In addition, the BI includes income statement items related to activities that produce operational risk that are omitted (eg P&L on the banking book) or netted (eg fee expenses, other operating expenses) in the GI.

Its really not bad math when you read it through although certainly banks will have questions about their specific applications. Unlike credit exposure risk measurements, the calculation relies on straight-forward ratios that banks already collect.
The next part of the model creates a bit more of the wincing that sometimes accompanies a Basel Committee publication. That’s because the methodology appears to move away from the pretty rational BI portion into a mushier Loss Multiplier and Loss Component. This is the part that we don’t like; creating ratios out of internal data makes sense, but throwing in hard numbers (“factors”) assigned by regulators seems like spitting into the wind. Will the Loss Multiplier and Loss Component mean anything? The Committee hopes so:

The introduction of the Loss Component into the framework not only enhances the SMA’s risk sensitivity, but also provides incentives for banks to improve operational risk management. Banks with more effective risk management and low operational risk losses will be required to hold a comparatively lower operational risk regulatory capital charge.

Again, the math is straight-forward. But this time we expect that banks will argue for and against the regulatory-assigned figures in the formula.
This paper is a good effort at standardizing bank risk metrics. Too bad they have to keep throwing these regulator-determined figures in there to hold the methodology together.
The full report is available at http://www.bis.org/bcbs/publ/d355.htm.

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